Printf("Pitched - Time = %f Memory = %i bytes \n", timerGPU. Test_kernel_Pitched_2D >(devPtrPitchedA, devPtrPitchedB, devPtrPitchedC, pitchA, pitchB, pitchC, Nrows, Ncols) Printf("Non-pitched - Time = %f Memory = %i bytes \n", timerGPU.GetCounter(), Nrows * Ncols * sizeof(float)) Test_kernel_2D >(devPtrA, devPtrB, devPtrC, Nrows, Ncols) GpuErrchk(cudaMemcpy2D(devPtrPitchedC, pitchC, hostPtrC, Ncols * sizeof(float), Ncols*sizeof(float), Nrows, cudaMemcpyHostToDevice)) ĭim3 gridSize(iDivUp(Ncols, BLOCKSIZE_x), iDivUp(Nrows, BLOCKSIZE_y)) ĭim3 blockSize(BLOCKSIZE_y, BLOCKSIZE_x) GpuErrchk(cudaMemcpy2D(devPtrPitchedB, pitchB, hostPtrB, Ncols * sizeof(float), Ncols*sizeof(float), Nrows, cudaMemcpyHostToDevice)) GpuErrchk(cudaMemcpy2D(devPtrPitchedA, pitchA, hostPtrA, Ncols * sizeof(float), Ncols*sizeof(float), Nrows, cudaMemcpyHostToDevice)) GpuErrchk(cudaMallocPitch(&devPtrPitchedC, &pitchC, Ncols * sizeof(float), Nrows)) GpuErrchk(cudaMallocPitch(&devPtrPitchedB, &pitchB, Ncols * sizeof(float), Nrows)) GpuErrchk(cudaMallocPitch(&devPtrPitchedA, &pitchA, Ncols * sizeof(float), Nrows)) - 2D pitched allocation and host->device memcopy GpuErrchk(cudaMemcpy(devPtrC, hostPtrC, Nrows * Ncols * sizeof(float), cudaMemcpyHostToDevice)) GpuErrchk(cudaMemcpy(devPtrB, hostPtrB, Nrows * Ncols * sizeof(float), cudaMemcpyHostToDevice)) GpuErrchk(cudaMemcpy(devPtrA, hostPtrA, Nrows * Ncols * sizeof(float), cudaMemcpyHostToDevice)) GpuErrchk(cudaMalloc(&devPtrC, Nrows * Ncols * sizeof(float))) ![]() GpuErrchk(cudaMalloc(&devPtrB, Nrows * Ncols * sizeof(float))) GpuErrchk(cudaMalloc(&devPtrA, Nrows * Ncols * sizeof(float))) Int tidy = blockIdx.y * blockDim.y + threadIdx.y Int tidx = blockIdx.x * blockDim.x + threadIdx.x _global_ void test_kernel_2D(float * _restrict_ devPtrA, float * _restrict_ devPtrB, float * _restrict_ devPtrC, const int Nrows, const int Ncols) The above results also show the increase in memory occupancy due to the use of pitched memory allocation. In addition, driver support for older generation GPUs with SM1.x has been deprecated. Q: How does this release differ from the current CUDA 6.5 Release A: This toolkit contain support for the GeForce GTX980 and GTX970. ![]() Pitched - Time = 20.418560 Memory = 65433600 bytesĪs it can be seen, there is not much difference in the two implementations for the two cards. A: The latest production drivers can be found and downloaded from our Latest NVIDIA Drivers Page. Below are the timing results for a GTX 960 card and a GT 920M cards. The reason for dealing with three matrices is the need to highlight memory transactions as compared to computation, so to highlight the differences between non-pitched and pitched allocations. ![]() In particular, the code performs the summation between three (non-pitched or pitched) matrices. The code below provides a performance testbench between the uses of non-pitched and pitched memories. However, for most recent compute capabilities, pitched memory allocation does not seem to lead to a relevant speedup. As already indicated by kangshiyin, the improvements arising from the use of cudaMallocPitch depend on the compute capability and are expected to be more significant for older ones.
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